One More (Yet-another?) Olympic Medal Live-tracking Shiny App

– use the Google spreadsheet data-munging “hack” from the [previous post](http://rud.is/b/2014/02/11/live-google-spreadsheet-for-keeping-track-of-sochi-medals/) in a Shiny context
– include it seamlessly into a web page, and
– run it locally without a great deal of wrangling

The code for the app is [in this gist](https://gist.github.com/hrbrmstr/8949172). It is unsurprisingly just like [some spiffy other code](http://www.r-bloggers.com/winter-olympic-medal-standings-presented-by-r/) you’ve seen apart from my aesthetic choices (Sochi blue! lines+dots! and, current rankings next to country names).

I won’t regurgitate the code here since it’s just as easy to view on [github](https://gist.github.com/hrbrmstr/8949172). You’re seeing the live results of the app below (unless you’ve been more conservative than most folks with your browser security settings),

but the app is actually hosted over at [Data Driven Security](http://shiny.dds.ec/sochi2014/), a blog and (woefully underpowered so reload if it coughs up blood, pls) Shiny server that I run with @jayjacobs. It appears in this WordPress post with the help of an `IFRAME`. It’s essentially the same technique the RStudio/Shiny folks use in many of their own examples.

The app uses [bootstrapPage()](http://www.rdocumentation.org/packages/shiny/functions/bootstrapPage) to help make a more responsive layout which will react nicely in an `IFRAME` setting (since you won’t know the width of the browser area you’re trying to fit the Shiny output into).

In the `ui.R` file, I have the [plotOutput()](http://www.rdocumentation.org/packages/shiny/functions/plotOutput) configured to scale to 100% of container width:

The *really cool* part (IMO) about many Shiny apps is that you don’t need to rely on the external server to work with the visualization/output. Provided that:

– the authors have coded their app to support local execution…
– and presented the necessary `ui.R`, `server.R`, `global.R`, HTML/CSS & data files either as a github gist or a zip/gz/tar.gz file…
– and **you** have the necessary libraries installed

then, you can start the app with a simple [Rscript](http://www.rdocumentation.org/packages/utils/functions/Rscript) one-liner:

There is *some* danger doing this if you haven’t read through the R code prior, since it’s possible to stick some fairly malicious operations in an R script (hey, I’m an infosec professional, so we’re always paranoid :-). But, if you stick with using a gist and do examine the code, you should be fine.